BEST : A decision tree algorithm that handles missing values

DOI10.48550/arXiv.1804.10168zbMath1505.62055arXiv1804.10168OpenAlexW3102208177MaRDI QIDQ143925

Jeffrey S. Rosenthal, Cédric Beaulac, Cédric Beaulac, Jeffrey S. Rosenthal

Publication date: 26 April 2018

Published in: Computational Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1804.10168

zbMATH Keywords

missing dataclassification and regression treeinterpretable modelsapplied machine learningvariable importance analysis

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Learning and adaptive systems in artificial intelligence (68T05)

Related Items (2)

Imputation Scores ⋮ BESTree

Uses Software

• R
• ggplot2
• rpart
• C50
• MICE
• C4.5
• sinaplot

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Bagging predictors
• What is meant by ``missing at random?
• ggplot2
• SinaPlot: An Enhanced Chart for Simple and Truthful Representation of Single Observations Over Multiple Classes
• Inference and missing data
• Understanding Machine Learning
• Extremely randomized trees
• Random forests

This page was built for publication: BEST : A decision tree algorithm that handles missing values